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EP-4740619-A1 - METHOD AND SYSTEM FOR REGULATING AN ENERGY CONSUMPTION IN A HETEROGENEOUS NETWORK (HETNET) ENVIRONMENT

EP4740619A1EP 4740619 A1EP4740619 A1EP 4740619A1EP-4740619-A1

Abstract

The present disclosure relates to a method [400] and a system [300] for regulating an energy consumption in a Heterogeneous Network (HetNet) environment The present disclosure encompasses: monitoring [404], by a processing unit [302], traffic levels at one or more cell sites in a network region, said monitoring corresponds to evaluating a set of KPIs; predicting [406], by the processing unit [302], the one or more traffic levels; identifying [408], by the processing unit [302] via an identification unit [304], a candidate cell site and a set of neighbouring cell sites based on the one or more traffic levels; determining [410], by the processing unit [302], a coverage hole flag; and automatically switching [412], by the processing unit [302], between a power ON state and a power OFF of the identified candidate cell site based on the coverage hole flag to regulate the energy consumption and maintain a pre-defined operational criterion.

Inventors

  • SHAH, BRIJESH
  • BHATNAGAR, PRADEEP KUMAR
  • BHATNAGAR, AAYUSH
  • Pandey, Anupkumar

Assignees

  • Jio Platforms Limited

Dates

Publication Date
20260513
Application Date
20240704

Claims (20)

  1. 1. A method [400] for regulating an energy consumption in a Heterogeneous Network (HetNet) environment, the method [400] comprising: monitoring [404], by a processing unit [302], one or more traffic levels at one or more cell sites in a network region, wherein said monitoring corresponds to evaluating a set of Key Performance Indicators (KPIs) associated with the one or more cell sites; predicting [406], by the processing unit [302], one or more traffic levels associated with each of the one or more cell sites; identifying [408], by the processing unit [302] via an identification unit [304], a candidate cell site and a set of neighbouring cell sites based on the predicted one or more traffic levels; determining [410], by the processing unit [302], a coverage hole flag associated with the identified candidate cell site and the set of neighbouring cell sites; and automatically switching [412], by the processing unit [302], between a power ON state and a power OFF state of the identified candidate cell site based on the determined coverage hole flag.
  2. 2. The method [400] as claimed in claim 1, wherein the automatically switching [410], by the processing unit [302], between the power ON state and the power OFF state of the identified candidate cell site, maintains a pre-defined operational criterion associated with the HetNet environment.
  3. 3. The method [400] as claimed in claim 1, further comprising: analysing, by the processing unit [302], the one or more traffic levels of the one or more cell sites to identify one of a period of minimal traffic level and a period of no traffic level; evaluating, by the processing unit [302], the energy consumption during one of the identified period of minimal traffic level and the period of no traffic level, wherein the energy consumption is evaluated against a predefined efficiency threshold; predicting, by the processing unit [302], one of a target period of minimal traffic level and a target period of no traffic level, based on one or more historical traffic level patterns and an associated energy usage; and adjusting, by the processing unit [302], the automatically switching between the power ON state and the power OFF state of the identified candidate cell site during one of the predicted target period of minimal traffic level and the predicted target period of no traffic level.
  4. 4. The method [400] as claimed in claim 1, wherein the set of KPIs comprises at least one of a Physical Resource Block (PRB) Utilization, a Number of Radio Resource Control (RRC) Users, a number of active users, a Cell effective throughput, and a Total traffic (Uplink and Downlink).
  5. 5. The method [400] as claimed in claim 1, wherein the predicting further comprises implementing, by the processing unit [302], one or more supervised machine learning techniques, comprising at least a support vector technique implemented via a Support Vector Machine (SVM), wherein the support vector technique is implemented to anticipate a user data based on a historical traffic level data, a day of week, and a time, utilizing a kernel function to consider both a spatial distance and a temporal distance between one or more data points.
  6. 6. The method [400] as claimed in claim 1, wherein the automatically switching between the power ON state and the power OFF state is further based on evaluating, by the processing unit, a coverage, and an overlap impact that occurs when the candidate site is switched OFF or ON to ensure no coverage hole is created that affect user experience.
  7. 7. The method [400] as claimed in claim 1, wherein the identifying the candidate cell site and the set of neighbouring cell sites comprises evaluating at least one of: a measurement range of a signal strength and a site location, based on one or more variations in one or more traffic level patterns over a time, a day of week, and one or more seasonal changes.
  8. 8. The method [400] as claimed in claim 1, wherein the determining the coverage hole flag comprises evaluation of a planning data and a crowdsourcing data comprising one or more parameters, wherein the one or more parameters comprises at least one of a best server plot (latitude and longitude of a site location) and a signal strength, to tag one or more areas with a received signal strength less than -110 as one or more potential coverage holes.
  9. 9. The method [400] as claimed in claim 1, wherein for the automatically switching between the power ON state and the power OFF state, the method [400] further comprises: deactivating the identified candidate cell site; triggering a handover mechanism to ensure a seamless transition of one or more users to the set of neighbouring cell sites; and updating a network configuration to reflect deactivation of a macro 5G new radio (NR) node B (gNB).
  10. 10. The method [400] as claimed in claim 9, wherein subsequent to the automatically switching, the method further comprises: continuously monitoring, by the processing unit [302], of at least one of: the one or more traffic levels; a network performance; and a user experience of the set of neighbouring cell sites, wherein the continuously monitoring of the one or more traffic levels, the network performance, and the user experience enables assessing of a traffic level distribution and a capacity utilization in the set of neighbouring cell sites; and reactivating, by the processing unit [302], the macro 5G new radio (NR) node B (gNB) of the candidate cell site when the predicted or actual one or more traffic levels of a set of neighbour gNBs corresponding to the set of neighbouring cell sites increases above a predefined threshold.
  11. 11. A system [300] for regulating an energy consumption in a Heterogeneous Network (HetNet) environment, the system [300] comprising: a processing unit [302], configured to: monitor one or more traffic levels at one or more cell sites in a network region, wherein said monitoring corresponds to evaluating a set of Key Performance Indicators (KPIs) associated with the one or more cell sites; predict one or more traffic levels associated with each of the one or more cell sites; identify, via an identification unit [304], a candidate cell site and a set of neighbouring cell sites based on the predicted one or more traffic levels; determine a coverage hole flag associated with the identified candidate cell site and the set of neighbouring cell sites; and automatically switch between a power ON state and a power OFF state of the identified candidate cell site based on the determined coverage hole flag.
  12. 12. The system [300] as claimed in claim 11, wherein the automatically switch between the power ON state and the power OFF state of the identified candidate cell site maintains a predefined operational criterion associated with the HetNet environment.
  13. 13. The system [300] as claimed in claim 11, wherein the processing unit [302] is further configured to: analyse the one or more traffic levels of the one or more cell sites to identify one of a period of minimal traffic level and a period of no traffic level; evaluate the energy consumption during one of the identified period of minimal traffic level and the period of no traffic level, wherein the energy consumption is evaluated against a predefined efficiency threshold; predict one of a target period of minimal traffic level and a target period of no traffic level, based on one or more historical traffic patterns and an associated energy usage; and adjust the automatically switching the power ON state and power OFF state of the identified candidate cell site during one of the predicted target period of minimal traffic level and the predicted target period of no traffic level.
  14. 14. The system [300] as claimed in claim 11, wherein the set of KPIs comprises at least one of a Physical Resource Block (PRB) Utilization, a number of Radio Resource Control (RRC) Users and a number of active users, a Cell effective throughput, and a Total traffic (Uplink and Downlink).
  15. 15. The system [300] as claimed in claim 11, wherein to predict, the processing unit [302] is further configured to implement one or more supervised machine learning techniques comprising at least a support vector technique implemented via a Support Vector Machine (SVM), wherein the support vector technique is implemented to anticipate a user data based on a historical traffic data, a day of week, and a time, utilizing a kernel function to consider both a spatial distance and a temporal distance between one or more data points.
  16. 16. The system [300] as claimed in claim 11, wherein to automatically switch, the processing unit [302] is further configured to evaluate a coverage and an overlap impact that occurs when the candidate site is switched OFF or ON to ensure no coverage hole is created that affect user experience.
  17. 17. The system [300] as claimed in claim 11, wherein to identify the candidate cell site and the set of neighbouring cell sites, the processing unit [302] is configured to evaluate a measurement range of a signal strength and a site location, based on one or more variations in one or more traffic level patterns over a time, a day of week, and one or more seasonal changes.
  18. 18. The system [300] as claimed in claim 11, wherein to determine the coverage hole flag, the processing unit [302] is further configured to evaluate a planning data and a crowdsourcing data comprising one or more parameters, wherein the one or more parameters comprises a best server plot (latitude and longitude of a site location) and a signal strength, to tag one or more areas with a received signal strength less than -110 as one or more potential coverage holes.
  19. 19. The system [300] as claimed in claim 11, wherein to automatically switch, the processing unit [302] is configured to deactivate the identified candidate cell site, triggering a handover mechanism to ensure a seamless transition of one or more users to the set of neighbouring cell sites, and updating a network configuration to reflect deactivation of a macro 5G new radio (NR) node B (gNB).
  20. 20. The system [300] as claimed in claim 19, wherein subsequent to the automatically switching, the processing unit [302] is further configured to continuously monitor the one or more traffic levels, a network performance, and a user experience of the set of neighbouring cell sites, wherein the continuously monitoring of the one or more traffic levels, the network performance, and the user experience enables assessing of a traffic level distribution and a capacity utilization in the set of neighbouring cell sites; and reactivate the macro 5G new radio (NR) node B (gNB) of the candidate cell site when the predicted or actual one or more traffic levels of a set of neighbour gNBs corresponding to the set of neighbouring cell sites increases above a predefined threshold.

Description

METHOD AND SYSTEM FOR REGULATING AN ENERGY CONSUMPTION IN A HETEROGENEOUS NETWORK (HETNET) ENVIRONMENT TECHNICAL FIELD [0001] Embodiments of the present disclosure generally relate to network performance management systems. More particularly, embodiments of the present disclosure relate to methods and systems for regulating an energy consumption in a Heterogeneous Network (HetNet) environment. BACKGROUND [0002] The following description of the related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section is used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of the prior art. [0003] Wireless communication technology has rapidly evolved over the past few decades, with each generation bringing significant improvements and advancements. The first generation of wireless communication technology was based on analog technology and offered only voice services. However, with the advent of the second generation (2G) technology, digital communication and data services became possible, and text messaging was introduced. The third generation (3G) technology marked the introduction of high-speed internet access, mobile video calling, and location-based services. The fourth generation (4G) technology revolutionized wireless communication with faster data speeds, better network coverage, and improved security. Currently, the fifth generation (5G) technology is being deployed, promising even faster data speeds, low latency, and the ability to connect multiple devices simultaneously. With each generation, wireless communication technology has become more advanced, sophisticated, and capable of delivering more services to its users. [0004] Energy efficiency is a critical consideration for cell site operations, particularly when it comes to the switch on/off process of a cell site. Cell sites consume a significant amount of energy, and inefficient switch on/off procedures can result in unnecessary power consumption and increased operational costs. In a typical cellular network, one can easily see that the traffic demand in the peak hours is much higher than that at night, which inspires the different rates offered by cellular operators. To address this mismatch in demand, optimizing energy efficiency during the cell site switch on/off process is essential. [0005] Further, over the period of time various solutions have been developed to improve the performance of communication devices and to ensure energy efficiency. However, there are certain challenges with existing solutions. Firstly, proper equipment management and maintenance play a crucial role in energy efficiency. Regular inspections and maintenance activities help identify and address any issues that may contribute to excessive power consumption during the switch on/off process. However, ensuring that equipment is operating at its optimum efficiency, such as utilizing energy-saving features and implementing power management protocols, is a humongous task. Furthermore, adopting energy-efficient hardware and components can contribute to overall energy savings during the switch on/off process but is an expensive process. [0006] In the current existing solutions, continuous monitoring and data analysis are key for identifying areas for energy optimization. By collecting and analyzing real-time data on energy usage, site performance, and environmental factors, operators can gain insights into energy patterns and make informed decisions to improve efficiency. However, this requires a lot of manual intervention. [0007] Thus, there exists an imperative need in the art to implement smart automation and intelligent solutions that can improve energy efficiency. SUMMARY [0008] This section is provided to introduce certain aspects of the present disclosure in a simplified form that are further described below in the detailed description. This summary is not intended to identify the key features or the scope of the claimed subject matter. [0009] An aspect of the present disclosure may relate to a method for regulating an energy consumption in a Heterogeneous Network (HetNet) environment. The method comprises monitoring, by a processing unit, one or more traffic levels at one or more cell sites in a network region, wherein said monitoring corresponds to evaluating a set of Key Performance Indicators (KPIs) associated with the one or more cell sites. The method further comprises predicting, by the processing unit, the one or more traffic levels associated with each of the one or more cell sites. The method further comprises identifying, by the processing unit, via an identification unit, a candidate cell site and a set of neighbouring cell sites based on the predicted one or more traffic levels. The method furth